First Ever Technology Recognizes Disease Biomarkers Directly in Menstrual Blood in Sanitary Towels

8 billion people menstruate worldwide, yet menstrual blood has been largely overlooked in medical practice. This blood contains hundreds of proteins, many of which correlate with their concentration in venous blood. Various diseases, including cancers like ovarian cancer and conditions such as endometriosis, cause specific proteins to appear in the blood, which can serve as biomarkers for disease detection. Despite its potential, menstrual blood has always been considered waste. Now, a groundbreaking development enables the detection of disease biomarkers in menstrual blood – directly in sanitary towels.

Researchers at ETH Zurich (Zurich, Switzerland have developed MenstruAI, a pioneering device capable of recognizing biomarkers in menstrual blood. This electronic-free sensor technology eliminates the need for laboratory analysis and could enable early disease detection in daily life. MenstruAI is the first to make menstrual health data systematically usable, marking a significant step towards improving women’s health. The process is straightforward: wear the sanitary towel with the embedded non-electronic sensor, take a photo of the used towel with a smartphone, and then use an app to analyze the results. MenstruAI is designed to allow users to check their health regularly and easily, integrating a health tracking tool into an unexpected place: the sanitary towel.

The ETH team used three biomarkers to develop MenstruAI: C-reactive protein (CRP), a general inflammation marker; CEA, a tumor marker elevated in various cancers; and CA-125, a protein that can indicate endometriosis and ovarian cancer. More protein-based biomarkers are being studied and will be added to broaden the scope of health indicators. MenstruAI uses a paper-based rapid test strip, similar to Covid self-tests, but instead analyzes blood rather than saliva. When a biomarker in the menstrual blood contacts a specific antibody on the test strip, a colored indicator forms. The color’s intensity varies depending on the biomarker concentration—darker colors indicate higher concentrations. The test area is housed in a flexible silicone chamber that attaches to a commercially available sanitary towel. The design ensures that only a controlled amount of blood reaches the sensor, preventing smearing or distortion of results.

The results are visible to the naked eye or can be analyzed using a machine learning-based app that assesses the color intensity and detects subtle differences in protein amounts. This app makes the results objectively measurable. Following an initial feasibility study with volunteers, the team is planning a larger field study with over 100 participants. The goal is to assess the usability of MenstruAI in real-world conditions and to compare its results with those of established laboratory methods. Another critical area of focus is the biological variability of menstrual blood, which changes based on the day of the cycle and from person to person. This variability must be understood and analyzed as part of the clinical validation process.

Additionally, regulatory requirements for potential market approval, including biocompatibility assessments, must be addressed. However, the materials used are considered safe. The team is also collaborating with design experts to refine the user experience, aiming to minimize psychological barriers for users. MenstruAI operates without the need for laboratory equipment and can serve as an early warning system—users can seek medical advice if abnormal values are detected. It is not intended to replace traditional diagnostics but to help users decide when it may be necessary to consult a doctor. Furthermore, MenstruAI can track health trends over time, offering valuable insights into any changes.

“To date, menstrual blood has been regarded as waste. We are showing that it is a valuable source of information,” said Lucas Dosnon, first author and doctoral student.

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ETH Zurich